HyDNN: A Hybrid Deep Learning Framework Based Multiuser Uplink Channel Estimation and Signal Detection for NOMA-OFDM System-Reference-Cited by-同舟云学术

HyDNN: A Hybrid Deep Learning Framework Based Multiuser Uplink Channel Estimation and Signal Detection for NOMA-OFDM System

Published:2023 Issue: Volume:11 Page:66742-66755
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Rahman Md Habibur¹^ORCID,Sejan Mohammad Abrar Shakil¹^ORCID,Aziz Md Abdul¹^ORCID,You Young-Hwan²^ORCID,Song Hyoung-Kyu¹^ORCID

Affiliation:

1. Department of Information and Communication Engineering, Sejong University, Seoul, Republic of Korea

2. Department of Convergence Engineering for Intelligent Drone, Sejong University, Seoul, Republic of Korea

Funder

Information and Communication Technology (ICT) Research and Development Program of Ministry of Science and Technology/ Information and Communications Technology Promotion (MSIT/IITP)

Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10167605.pdf?arnumber=10167605

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1. Deep Learning for Ultra-Reliable and Low-Latency Communications in 6G Networks

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